Open Source and Vertica
The open-source community is a large and diverse collaboration, comprised of talented software specialists dedicated to advancing the possibilities of code written outside of considerations for any immediate profit. Virtually all commercial software vendors rely on open-source contributions to move their projects forward, based on the constant innovations and improvements that this community provides.
Recognizing these important contributions, Vertica has established the Vertica Open-Source Fund to reward open source contributors that support the capabilities of advanced data analytics and machine learning.

How the Vertica Open-Source Fund Works
All open-source projects eligible for recognition under this program will first be hosted on GitHub, and therefore made available to the Vertica community. Once they are hosted on GitHub, the nomination process will begin with Vertica developers nominating projects to be considered for the fund.
The Fund selection committee will select the final recipients
Nomination Process Details
Eligible projects include those that:
Evaluation
The Vertica Open Source Fund board will review nominations on a monthly basis. Awards will be based on such factors as (not an exhaustive list):
- Ease of integration [with Vertica]
- Originality
- Popularity inside Vertica
- Popularity of the project as hosted on GitHub
- Most important: Usefulness in advancing a data analytics capability, either by enhancing that capability, or by offering an original utility useful to Vertica practitioners
Community awareness
With permission, each project and project team award will be made public on this site, noting the level of recognition. Monetary value will remain undisclosed. Awarded projects will also be recognized on GitHub.
“The open-source community plays a substantial role in driving innovation for Vertica and the tech community as a whole, and many of those open-source developer contributions are taken for granted. The Vertica Open-Source Fund seeks to give back to the open-source community and recognize deserving contributions.“
Rohit Amarnath, Chief Technology Officer
Vertica

Some Examples of Open-Source Projects Vertica Values
Some open-source capabilities are central to the power of Vertica to manage and analyze data. In many cases, our partners or independent people created projects that vastly extend Vertica’s capabilities. Those are the sorts of projects that would be eligible for the open source fund awards. Many of the projects that Vertica manages and adds contributions to were originally created in that way. While the projects below are no longer eligible for the award, we still want to call out some of our favorite projects.
In particular, we would like to highlight the Vertica Spark and Vertica Kafka connectivities. These are used in a high percentage of Vertica installations, both installations of the commercial version the Vertica Analytics Platform, and the free Vertica community edition. The Vertica GitHub page includes several more projects.
Another open-source star is VerticaPy. This is a python library that lets you do standard data science interactive and exploratory workloads in code similar to pandas and scikit learn, using a Jupyter notebook interface, and using the power of the Vertica engine and built-in highly performant distributed machine learning functions and algorithms. This allows you to do all work inside the database, without having the overhead of moving data around, or being limited to small data samples by the memory size of a single computer or sandbox.
Vertica is also fully containerized. The open source Vertica community edition container is available on dockerhub and github. Kubernetes operators, helm charts, and many other aspects of running Vertica in a container can be found on Github vertica-containers. To make things a bit simpler, a complete Jupyter-Lab with Vertica, VerticaPy, and other essentials in one package is now available.
In addition, there is a curated list, Awesome-Vertica, of many open-source projects in a wide variety of areas, from Vertica clients and APIs (Go, Python, Node.js) to tools like the library to parse Hive and Presto SQL, to example projects like our geospatial example application.
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